Mastering PyCharm Transcripts
Chapter: Data science tools
Lecture: Your turn: Data science

Login or purchase this course to watch this video and the rest of the course contents.
0:02 The data science tools are fun to play with
0:04 because we get to draw cool pictures,
0:06 so in this your turn, you'll get to create some cool looking crafts like this
0:10 and draw them in PyCharm, both directly within PyCharm
0:14 and by using PyCharm's embedded Jupyter notebooks.
0:19 Go down, you can see your steps are here,
0:22 so we're going to start up by using PyCharm's data science mode
0:26 and if we just start working with the data science libraries
0:28 we saw it will actually suggest and adapt to that directly,
0:32 we'll draw some cool graphs and then we'll do the same thing
0:35 but this time we'll redo it again but in Jupyter notebooks
0:38 and there are a few minor changes to make things work the way you might want.
0:41 So we'll start out aiming to draw this picture
0:44 we're going to use Pandas, Matplotlib and so on,
0:47 so create a new project, we're going to write this import up here
0:51 and then we're going to important NumPy and once we do that
0:54 it says, oh, NumPy science, you want to be scientific
0:57 and go into scientific mode, yes, you do, click that.
1:00 So then we're going to add this remaining imports,
1:03 we're going to write some code here
1:05 to create like a three dimensional parabola,
1:08 sort of inverted quadratic equation type thing
1:10 and we're going to put it here,
1:13 you might get a warning about arange, don't worry it should be working,
1:18 PyCharm just doesn't detect that correctly for whatever reason
1:20 you want to create a surface and show it and it should look like this in PyCharm,
1:24 you also get a warning about this color map coolwave, also, it's fine.
1:28 So you get this working, this is really cool, over here in this science view,
1:32 now we're going to do the same thing in Jupyter notebooks,
1:35 so we're going to create a new Jupyter notebook,
1:37 and the code is slightly different, you want to tell Matplotlib to render inline
1:41 you have to do a few steps to actually install and set up Jupyter notebooks,
1:45 so that's pretty interesting,
1:48 there's a few things we got to do here,
1:50 notice there is this fix button you have to click,
1:52 it is going to do some work, it's going to eventually be ready to run
1:55 once you click run, you'll be able to use this url,
1:58 you don't actually have to click it though, you just go and rerun,
2:02 there's a little button that's hiding right here, a little green button,
2:06 you just click that again, it will automatically connect, that's awesome.
2:09 And then you'll go and write the rest of the code
2:12 you don't have to do the service.show this time
2:15 because Jupyter knows about it already
2:17 and down here embedded within our Jupyter notebook
2:19 is basically the same output, it's pretty cool.
2:22 So, have fun drawing pretty pictures with PyCharm.